SenSync: Real-Time and Accurate Passive Sensing

SenSync tackles key challenges in RFID-based differential sensing systems, including temporal misalignment, phase ambiguity, and environmental sensitivity. Traditional techniques are limited by sequential data processing, which introduces time shifts, and arbitrary phase jumps injected by commercial RFID readers, which obscure accurate differential measurements. These issues, compounded by multipath effects and dynamic environments, hinder the deployment of robust RFID sensing systems at scale. To address these challenges, we propose innovative algorithms and signal processing techniques to align and interpret time-shifted data from multiple ICs. Our approach mitigates the effects of temporal misalignment and phase ambiguity, ensuring reliable differential sensing in real-world applications. By improving data alignment and robustness, we accelerate the sensory resolution by 5 x. Furthermore, we developed a user interface capable of automatically detecting sensors within the system's field of operation and displaying their readings in real-time, demonstrating the practical applicability and versatility of our proposed solution.

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Publication Details

Published
2025-04-22
DOI
https://doi.org/10.1109/rfid64926.2025.11015540
Citations
1
Primary Topic
Sensor Technology and Measurement Systems
Type
article
Field-Weighted Citation Impact
1.49
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SenSync: Real-Time and Accurate Passive Sensing

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article

SenSync: Real-Time and Accurate Passive Sensing

Dinesh Bharadia, Harine Govindarajan, Nagarjun Bhat, Agrim Gupta, Ishan Bansal
article en
1 citations

Abstract

SenSync tackles key challenges in RFID-based differential sensing systems, including temporal misalignment, phase ambiguity, and environmental sensitivity. Traditional techniques are limited by sequential data processing, which introduces time shifts, and arbitrary phase jumps injected by commercial RFID readers, which obscure accurate differential measurements. These issues, compounded by multipath effects and dynamic environments, hinder the deployment of robust RFID sensing systems at scale. To address these challenges, we propose innovative algorithms and signal processing techniques to align and interpret time-shifted data from multiple ICs. Our approach mitigates the effects of temporal misalignment and phase ambiguity, ensuring reliable differential sensing in real-world applications. By improving data alignment and robustness, we accelerate the sensory resolution by 5 x. Furthermore, we developed a user interface capable of automatically detecting sensors within the system's field of operation and displaying their readings in real-time, demonstrating the practical applicability and versatility of our proposed solution.

University of California San Diego (US)
Openalex Percentile: Top 17%
Sensor Technology and Measurement Systems
1.49
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SenSync: Real-Time and Accurate Passive Sensing — Dinesh Bharadia, Harine Govindarajan, et al. · (2025) | TGRS Research Map | TGRS